中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Limited memory filter for 3D relative position orientation estimation of maneuvering target

文献类型:会议论文

作者Hou FL(侯菲莉); Zhu F(朱枫)
出版日期2004
会议名称5th World Congress on Intelligent Control and Automation
会议日期June 15-19, 2004
会议地点Hangzhou, China
页码4427-4431
中文摘要In a vision-based positioning system, noise in the image features results in errors in 3D reconstruction, and thereby, causes a serious degradation in individual 3D object pose (position and orientation) estimation. To find a solution for this problem, a filter approach is presented for more accurate relative 3D pose estimation of a moving object with respect to the vision sensor system. Different from previous schemes that were limited to the assumption that the relative motion between the target and the camera is smooth and slow, this approach is implementable for a maneuvering target without a prior knowledge about its dynamics. And the computation load is much reduced by avoiding the need of EFK. This filter is composed of a maneuver detector and a filter updater. First, by analyzing the effect of image noise on the pose estimate error, linear measure equations relating the nominal pose parameters (obtained by 3D reconstruction) and the true ones are proposed. Then, a maneuver detector of maximum detection probability is deduced, and two sub-optimal detectors for quick maneuver and slow maneuver are further developed respectively. When a maneuver is declared, updating is performed with limited memory filtering. Experiment results verify the effectiveness of this approach.
收录类别EI
产权排序1
会议主办者IEEE
会议录Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
会议录出版者IEEE
会议录出版地New York
语种英语
源URL[http://ir.sia.cn/handle/173321/7992]  
专题沈阳自动化研究所_光电信息技术研究室
推荐引用方式
GB/T 7714
Hou FL,Zhu F. Limited memory filter for 3D relative position orientation estimation of maneuvering target[C]. 见:5th World Congress on Intelligent Control and Automation. Hangzhou, China. June 15-19, 2004.

入库方式: OAI收割

来源:沈阳自动化研究所

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